This course focuses on modeling, quantification, and analysis of uncertainty by teaching random variables, simple random processes and their probability distributions, Markov processes, limit theorems, elements of statistical inference, and decision making under uncertainty.

In this course, which was designed for graduate students who use statistics in their research, students learn how to select the appropriate test statistics determine the degree of statistical inference allowed by the data.